Articles | Volume 16, issue 5
https://doi.org/10.5194/esd-16-1483-2025
https://doi.org/10.5194/esd-16-1483-2025
Research article
 | 
11 Sep 2025
Research article |  | 11 Sep 2025

Simple physics-based adjustments reconcile the results of Eulerian and Lagrangian techniques for moisture tracking in atmospheric rivers

Alfredo Crespo-Otero, Damián Insua-Costa, Emilio Hernández-García, Cristóbal López, and Gonzalo Míguez-Macho

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Cited articles

American Meteorological Society: Atmospheric River, Glossary of Meteorology, https://glossary.ametsoc.org/wiki/Atmospheric_river (last access: 30 May 2025), 2025. 
Blamey, R. C., Ramos, A. M., Trigo, R. M., Tomé, R., and Reason, C. J. C.: The Influence of Atmospheric Rivers over the South Atlantic on Winter Rainfall in South Africa, J. Hydrometeorol., 19, 127–142, https://doi.org/10.1175/JHM-D-17-0111.1, 2018. 
Bonne, J.-L., Steen-Larsen, H. C., Risi, C., Werner, M., Sodemann, H., Lacour, J.-L., Fettweis, X., Cesana, G., Delmotte, M., Cattani, O., Vallelonga, P., Kjær, H. A., Clerbaux, C., Sveinbjörnsdóttir, Á. E., and Masson-Delmotte, V.: The summer 2012 Greenland heat wave: In situ and remote sensing observations of water vapor isotopic composition during an atmospheric river event, J. Geophys. Res.-Atmos., 120, 2970–2989, https://doi.org/10.1002/2014JD022602, 2015. 
Brioude, J., Arnold, D., Stohl, A., Cassiani, M., Morton, D., Seibert, P., Angevine, W., Evan, S., Dingwell, A., Fast, J. D., Easter, R. C., Pisso, I., Burkhart, J., and Wotawa, G.: The Lagrangian particle dispersion model FLEXPART-WRF version 3.1, Geosci. Model Dev., 6, 1889–1904, https://doi.org/10.5194/gmd-6-1889-2013, 2013. 
Cloux, S., Garaboa-Paz, D., Insua-Costa, D., Miguez-Macho, G., and Pérez-Muñuzuri, V.: Extreme precipitation events in the Mediterranean area: contrasting two different models for moisture source identification, Hydrol. Earth Syst. Sci., 25, 6465–6477, https://doi.org/10.5194/hess-25-6465-2021, 2021. 
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Short summary
We evaluated two Lagrangian moisture tracking tools for computing moisture sources in precipitation events related to atmospheric rivers (ARs) and compared them against the Weather Research and Forecasting (WRF) model with water vapor tracers. Our results show that both tools (the Sodemann et al., 2008, and Dirmeyer and Brubaker, 1999, methodologies) present a systematic underestimation of remote sources.  Implementing simple physics-based changes substantially improved both methods, narrowing the disparities among all approaches.
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